An On-the-fly Provenance Tracking Mechanism for Stream Processing Systems

Applications that operate over streaming data withhigh-volume and real-time processing requirements are becomingincreasingly important. These applications process streamingdata in real-time and deliver instantaneous responses to supportprecise and on-time decisions. In such systems, traceability -the ability to verify and investigate the source of a particularoutput - in real-time is extremely important. This ability allowsraw streaming data to be checked and processing steps to beverified and validated in timely manner. Therefore, it is crucialthat stream systems have a mechanism for dynamically trackingprovenance - the process that produced result data - at executiontime, which we refer to as on-the-fly stream provenance tracking.In this paper, we propose a novel on-the-fly provenance trackingmechanism that enables provenance queries to be performeddynamically without requiring provenance assertions to be storedpersistently. We demonstrate how our provenance mechanismworks by means of an on-the-fly provenance tracking algorithm.The experimental evaluation shows that our provenance solutiondoes not have a significant effect on the normal processing ofstream systems given a 7% overhead. Moreover, our provenancesolution offers low-latency processing (0.3 ms per additionalcomponent) with reasonable memory consumption.<br/

Real-time irrigation decision-making and control for site-specific irrigation of cotton using a centre pivot, 2012/13

Automated, site-specific irrigation control systems provide opportunities to deliver irrigation requirements when and where they are needed in spatially variable fields. Site-specific irrigation hardware developed for centre pivots and lateral moves currently involves loading the site-specific irrigation volumes before the irrigation event. However, the required irrigation application often changes during the irrigation event depending on the time taken for the machine to pass over the field. The irrigation volume may be further refined and updated in real-time during the irrigation event using infield measurements (e.g. weather, soil-water) or measurements of the crop from sensors mounted on the irrigation machine (e.g. cameras). The real-time irrigation control framework 'VARIwise' automatically determines site-specific irrigation requirements using weather, soil-water and plant growth measurements. These use control strategies and crop production models to predict irrigation application that achieve the desired performance objective (e.g. maximise crop yield, water productivity). An adaptive control strategy trial was conducted on a span of a centre pivot on a cotton crop at Jondaryan, QLD in 2012/13 to demonstrate the integration of infield sensors with a real-time irrigation control system. This utilised real-time, Internet-enabled irrigation control hardware, weather data, soil-water sensors, irrigation machine mounted plant sensing systems and a processor running VARIwise. The plant sensing systems estimated plant density, flower count and boll count from images, and plant height from a distance sensor. The adaptive control trials produced an average yield improvement of 7%, and water use reductions of 4% compared with industry-standard irrigation treatment using FAO-56

Dosimetric Evaluation of a New Rotating Gamma System for Stereotactic Radiosurgery

Purpose: A novel rotating gamma stereotactic radiosurgery (SRS) system (Galaxy RTi) with real-time image guidance technology has been developed for high-precision SRS and frameless fractionated stereotactic radiotherapy (SRT). This work investigated the dosimetric quality of Galaxy by comparing both the machine treatment parameters and plan dosimetry parameters with those of the widely used Leksell Gamma Knife (LGK) systems for SRS. Methods: The Galaxy RTi system uses 30 cobalt-60 sources on a rotating gantry to deliver non-coplanar, non-overlapping arcs simultaneously while the LGK 4C uses 201 static cobalt-60 sources to deliver noncoplanar beams. Ten brain cancer patients were unarchived from our clinical database, which were previously treated on the LGK 4C. The lesion volume for these cases varied from 0.1 cm3 to 15.4 cm3. Galaxy plans were generated using the Prowess TPS (Prowess, Concord, CA) with the same dose constraints and optimization parameters. Treatment quality metrics such as target coverage (%volume receiving the prescription dose), conformity index (CI), cone size, shots number, beam-on time were compared together with DVH curves and dose distributions. Results: Superior treatment plans were generated for the Galaxy system that met our clinical acceptance criteria. For the 10 patients investigated, the mean CI and dose coverage for Galaxy was 1.77 and 99.24 compared to 1.94 and 99.19 for LGK, respectively. The beam-on time for Galaxy was 17.42 minutes compared to 21.34 minutes for LGK (both assuming dose rates at the initial installation). The dose fall-off is much faster for Galaxy, compared with LGK. Conclusion: The Galaxy RTi system can provide dose distributions with similar quality to that of LGK with less beam-on time and faster dose fall-off. The system is also capable of real-time image guidance at treatment position to ensure accurate dose delivery for SRS.Comment: 14 pages, 7 figure

Magnetically Levitated Microrobotic Mixer

Microfluidic systems, when combined with microrobots, offer enhanced precision in chemical synthesis by precisely controlling reaction conditions. These systems, when integrated with analytical tools, allow for real-time monitoring and are cost-efficient due to their minimal volume requirements, thereby reducing risks associated with hazardous chemicals. In our study, we have investigated the mixing efficiency of Thymolphthalein indicator with NaOH solution in a magnetically levitated microrobotic mixer. A PMMA microfluidic chip was used to transfer fluid containing two different solutions and achieve fast and efficient mixing. By adjusting five different flow rates and altering the rotational speeds of the microrobots, the mixing efficiency was observed. The studies were carried out under the laminar regime, with incompressible Newtonian flow rates and varying actuator speeds. The measurement of mixing efficiency was accomplished through the calculation of changes in pixel intensity observed in microscopic images acquired throughout the mixing process. The presence of the microrobots resulted in the best efficiency at 80.37% at 500 rpm and 7 mL/min flow rate. Their potential in advanced reactions, such as nanoparticle synthesis and encapsulation, suggests promising avenues for improving product yields.Comment: 5 pages, 2 figures, 1 tabl

Accurate Determination of Total Antimony Using ICP-MS and Optimization Its Extraction Efficiency From Reference and Soil Samples

Two independent digestion techniques (microwave acid digestion with HF and HCl, HNO3 and Na2O2 sintering, respectively) were applied to determine the total Sb concentration in a real soil sample and in reference materials: Icelandic Basalt (BIR-1), Cody Shale (SCo-1) and (Soil-7). ICP-MS was used to determine total antimony concentrations in the digested and the extracted solutions using external calibration and isotope dilution technique. The recoveries of Sb using HF in the acids digestion mixture in closed-vessels microwave digestion system were excellent and the concentrations are in very good agreement with certified or reported concentrations of reference materials. Using closed-vessels combined with microwave heating systems probably prevents the loss of volatile Sb compounds. The use of hydrogen fluoride with other strong acid can help dissociating insoluble antimony silicates. Different extraction reagents were tested for their ability to extract antimony using an ultrasonic bath namely: EDTA disodium salt, potassium hydroxide, citric acid monohydrate, pyridine-2,6-dicarboxylic acid, ammonium acetate, ammonium oxalate, ammonium thiocyanate, ammonium persulphate and di-ammonium hydrogen citrate. A 500 mmol L-1 solution of citric acid pH 1.08 proved to be the most efficient extractant. Optimization of the extraction conditions were investigated by studying the effect of pH, concentration, temperature, time of extraction, the ratio of sample mass to the volume of extractant and the number of consecutive extractions. As a result three consecutive extractions for a total time of 45 min at 80 ˚C was the most efficient condition for Sb extraction. Using these extraction conditions 61%, 3.7% RSD and 42%, 2.2% RSD (n=6) of the total antimony in the real soil and Soil-7 samples, respectively could be extracted

Dynamic Volume Rendering of Functional Medical Data on Dissimilar Hardware Platforms

In the last 30 years, medical imaging has become one of the most used diagnostic tools in the medical profession. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) technologies have become widely adopted because of their ability to capture the human body in a non-invasive manner. A volumetric dataset is a series of orthogonal 2D slices captured at a regular interval, typically along the axis of the body from the head to the feet. Volume rendering is a computer graphics technique that allows volumetric data to be visualized and manipulated as a single 3D object. Iso-surface rendering, image splatting, shear warp, texture slicing, and raycasting are volume rendering methods, each with associated advantages and disadvantages. Raycasting is widely regarded as the highest quality renderer of these methods. Originally, CT and MRI hardware was limited to providing a single 3D scan of the human body. The technology has improved to allow a set of scans capable of capturing anatomical movements like a beating heart. The capturing of anatomical data over time is referred to as functional imaging. Functional MRI (fMRI) is used to capture changes in the human body over time. While fMRI’s can be used to capture any anatomical data over time, one of the more common uses of fMRI is to capture brain activity. The fMRI scanning process is typically broken up into a time consuming high resolution anatomical scan and a series of quick low resolution scans capturing activity. The low resolution activity data is mapped onto the high resolution anatomical data to show changes over time. Academic research has advanced volume rendering and specifically fMRI volume rendering. Unfortunately, academic research is typically a one-off solution to a singular medical case or set of data, causing any advances to be problem specific as opposed to a general capability. Additionally, academic volume renderers are often designed to work on a specific device and operating system under controlled conditions. This prevents volume rendering from being used across the ever expanding number of different computing devices, such as desktops, laptops, immersive virtual reality systems, and mobile computers like phones or tablets. This research will investigate the feasibility of creating a generic software capability to perform real-time 4D volume rendering, via raycasting, on desktop, mobile, and immersive virtual reality platforms. Implementing a GPU-based 4D volume raycasting method for mobile devices will harness the power of the increasing number of mobile computational devices being used by medical professionals. Developing support for immersive virtual reality can enhance medical professionals’ interpretation of 3D physiology with the additional depth information provided by stereoscopic 3D. The results of this research will help expand the use of 4D volume rendering beyond the traditional desktop computer in the medical field. Developing the same 4D volume rendering capabilities across dissimilar platforms has many challenges. Each platform relies on their own coding languages, libraries, and hardware support. There are tradeoffs between using languages and libraries native to each platform and using a generic cross-platform system, such as a game engine. Native libraries will generally be more efficient during application run-time, but they require different coding implementations for each platform. The decision was made to use platform native languages and libraries in this research, whenever practical, in an attempt to achieve the best possible frame rates. 4D volume raycasting provides unique challenges independent of the platform. Specifically, fMRI data loading, volume animation, and multiple volume rendering. Additionally, real-time raycasting has never been successfully performed on a mobile device. Previous research relied on less computationally expensive methods, such as orthogonal texture slicing, to achieve real-time frame rates. These challenges will be addressed as the contributions of this research. The first contribution was exploring the feasibility of generic functional data input across desktop, mobile, and immersive virtual reality. To visualize 4D fMRI data it was necessary to build in the capability to read Neuroimaging Informatics Technology Initiative (NIfTI) files. The NIfTI format was designed to overcome limitations of 3D file formats like DICOM and store functional imagery with a single high-resolution anatomical scan and a set of low-resolution anatomical scans. Allowing input of the NIfTI binary data required creating custom C++ routines, as no object oriented APIs freely available for use existed. The NIfTI input code was built using C++ and the C++ Standard Library to be both light weight and cross-platform. Multi-volume rendering is another challenge of fMRI data visualization and a contribution of this work. fMRI data is typically broken into a single high-resolution anatomical volume and a series of low-resolution volumes that capture anatomical changes. Visualizing two volumes at the same time is known as multi-volume visualization. Therefore, the ability to correctly align and scale the volumes relative to each other was necessary. It was also necessary to develop a compositing method to combine data from both volumes into a single cohesive representation. Three prototype applications were built for the different platforms to test the feasibility of 4D volume raycasting. One each for desktop, mobile, and virtual reality. Although the backend implementations were required to be different between the three platforms, the raycasting functionality and features were identical. Therefore, the same fMRI dataset resulted in the same 3D visualization independent of the platform itself. Each platform uses the same NIfTI data loader and provides support for dataset coloring and windowing (tissue density manipulation). The fMRI data can be viewed changing over time by either animation through the time steps, like a movie, or using an interface slider to “scrub” through the different time steps of the data. The prototype applications data load times and frame rates were tested to determine if they achieved the real-time interaction goal. Real-time interaction was defined by achieving 10 frames per second (fps) or better, based on the work of Miller [1]. The desktop version was evaluated on a 2013 MacBook Pro running OS X 10.12 with a 2.6 GHz Intel Core i7 processor, 16 GB of RAM, and a NVIDIA GeForce GT 750M graphics card. The immersive application was tested in the C6 CAVE™, a 96 graphics node computer cluster comprised of NVIDIA Quadro 6000 graphics cards running Red Hat Enterprise Linux. The mobile application was evaluated on a 2016 9.7” iPad Pro running iOS 9.3.4. The iPad had a 64-bit Apple A9X dual core processor with 2 GB of built in memory. Two different fMRI brain activity datasets with different voxel resolutions were used as test datasets. Datasets were tested using both the 3D structural data, the 4D functional data, and a combination of the two. Frame rates for the desktop implementation were consistently above 10 fps, indicating that real-time 4D volume raycasting is possible on desktop hardware. The mobile and virtual reality platforms were able to perform real-time 3D volume raycasting consistently. This is a marked improvement for 3D mobile volume raycasting that was previously only able to achieve under one frame per second [2]. Both VR and mobile platforms were able to raycast the 4D only data at real-time frame rates, but did not consistently meet 10 fps when rendering both the 3D structural and 4D functional data simultaneously. However, 7 frames per second was the lowest frame rate recorded, indicating that hardware advances will allow consistent real-time raycasting of 4D fMRI data in the near future

Efficient Learning in Heterogeneous Internet of Things Ecosystems

The Internet of Things (IoT) is a growing network of heterogeneous devices, combining various sensing and computing nodes at different scales, which creates a large volume of data. Many IoT applications use machine learning (ML) algorithms to analyze the data. The high computational complexity of ML workloads poses significant computational challenges to IoT computing platforms, which tend to be less-powerful and resource-constrained devices. Transmitting such large volumes of data to the cloud also have various issues such as scalability, security and privacy. In this dissertation, we propose efficient solutions to perform the ML tasks while decreasing power consumption and improving performance. We first leverage the heterogeneous and interconnected nature of the IoT systems, where IoT applications run on many different architectures (e.g., X86 server or ARM-based edge device) while communicating with each other. We present a cross-platform power and performance prediction technique for intelligent task allocation. The proposed technique estimates the time-variant energy consumption with only 7% error across completely different architectures, enabling the intelligent task allocation that saves the energy consumption of 16.5% for state-of-the-art ML workloads.We next show how to further advance the learning procedures towards real-time and online processing by distributing such learning tasks onto the hierarchy of IoT devices. Our solution leverages brain-inspired high-dimensional (HD) computing to derive a new class oflearning algorithms that can easily run on IoT devices, while providing high accuracy comparable to the state-of-the-arts. We present that the HD-based learning algorithms can cover various real-world problems from conventional classification to other cognitive tasks beyond classical MLs such as DNA pattern matching. We demonstrate that the HD-based learning can enable secure, collaborative learning by efficiently distributing a large volume of learning tasks into heterogeneous computing nodes. We have implemented the proposed learning solution on various platforms while offering superior computing efficiency. For example, our solution achieves 486×and 7× performance improvements for each of the training and inference phases on a low-power ARM processor, as compared to state-of-the-art deep learning

Radiofrequency Thermoablation On Ex Vivo Animal Tissues: Changes on Isolated Swine Thyroids

The use of Radiofrequency thermoablation (RFA) for treating large thyroid nodules is limited by the modest efficiency of the available systems in terms of volume of the ablation zones (AZs). This increases the risk of incomplete ablation of the nodule. Systems employing perfused electrodes have been developed to increase the volume of the AZ. Aim of this study is to compare the size of the AZ induced by RFA systems using internally cooled perfused vs. non-perfused electrodes in swine thyroids. RFAs were performed on 40 freshly isolated swine thyroids using both systems. The perfused system was tested using 0.9% saline, 7% and 18% hypertonic saline solutions. Energy delivery to the tissue was stopped when tissue conductivity dropped (real life simulations) and after an established time of 20 seconds (controlled duration). Following RFA, thyroids were transversally and longitudinally cut. Photographs were taken for macroscopic morphometry of the ablated zones before and after formalin fixation, to evaluate tissue shrinkage. Microscopic morphometry was performed on PAS stained sections. In real life simulation experiments, gross morphometry revealed that AZs produced with electrodes perfused using 7.0% saline are larger compared to isotonic saline. Microscopically, all the conditions tested using the perfused system produced larger AZs compared to non-perfused system after 20 seconds of RFA. In conclusion, the perfusion with 7.0% NaCl solution increased the electrical conductivity of the tissue in real life simulations, resulting in larger ablated areas compared to the use of isotonic saline